Data Call Technologi Stock Market Value
| DCLT Stock | USD 0 0 84.62% |
| Symbol | Data |
Data Call 'What if' Analysis
In the world of financial modeling, what-if analysis is part of sensitivity analysis performed to test how changes in assumptions impact individual outputs in a model. When applied to Data Call's pink sheet what-if analysis refers to the analyzing how the change in your past investing horizon will affect the profitability against the current market value of Data Call.
| 11/16/2024 |
| 12/16/2024 |
If you would invest 0.00 in Data Call on November 16, 2024 and sell it all today you would earn a total of 0.00 from holding Data Call Technologi or generate 0.0% return on investment in Data Call over 30 days. Data Call is related to or competes with Arax Holdings, AppTech Payments, Datasea, AuthID, and Priority Technology. Data Call Technologies, Inc. provides real-time informationcontent through digital signage and kiosk networks in the Uni... More
Data Call Upside/Downside Indicators
Understanding different market momentum indicators often help investors to time their next move. Potential upside and downside technical ratios enable traders to measure Data Call's pink sheet current market value against overall market sentiment and can be a good tool during both bulling and bearish trends. Here we outline some of the essential indicators to assess Data Call Technologi upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 36.81 | |||
| Information Ratio | 0.1143 | |||
| Maximum Drawdown | 155.4 | |||
| Value At Risk | (29.41) | |||
| Potential Upside | 52.63 |
Data Call Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Data Call's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Data Call's standard deviation. In reality, there are many statistical measures that can use Data Call historical prices to predict the future Data Call's volatility.| Risk Adjusted Performance | 0.0956 | |||
| Jensen Alpha | 2.92 | |||
| Total Risk Alpha | (0.15) | |||
| Sortino Ratio | 0.074 | |||
| Treynor Ratio | (2.40) |
Data Call Technologi Backtested Returns
Data Call is out of control given 3 months investment horizon. Data Call Technologi secures Sharpe Ratio (or Efficiency) of 0.12, which denotes the company had a 0.12% return per unit of risk over the last 3 months. We were able to break down and interpolate twenty-seven different technical indicators, which can help you to evaluate if expected returns of 2.91% are justified by taking the suggested risk. Use Data Call Coefficient Of Variation of 843.91, mean deviation of 12.08, and Downside Deviation of 36.81 to evaluate company specific risk that cannot be diversified away. Data Call holds a performance score of 9 on a scale of zero to a hundred. The firm shows a Beta (market volatility) of -1.18, which means a somewhat significant risk relative to the market. As returns on the market increase, returns on owning Data Call are expected to decrease by larger amounts. On the other hand, during market turmoil, Data Call is expected to outperform it. Use Data Call value at risk, as well as the relationship between the skewness and day typical price , to analyze future returns on Data Call.
Auto-correlation | -0.6 |
Good reverse predictability
Data Call Technologi has good reverse predictability. Overlapping area represents the amount of predictability between Data Call time series from 16th of November 2024 to 1st of December 2024 and 1st of December 2024 to 16th of December 2024. The more autocorrelation exist between current time interval and its lagged values, the more accurately you can make projection about the future pattern of Data Call Technologi price movement. The serial correlation of -0.6 indicates that roughly 60.0% of current Data Call price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.6 | |
| Spearman Rank Test | 0.38 | |
| Residual Average | 0.0 | |
| Price Variance | 0.0 |
Data Call Technologi lagged returns against current returns
Autocorrelation, which is Data Call pink sheet's lagged correlation, explains the relationship between observations of its time series of returns over different periods of time. The observations are said to be independent if autocorrelation is zero. Autocorrelation is calculated as a function of mean and variance and can have practical application in predicting Data Call's pink sheet expected returns. We can calculate the autocorrelation of Data Call returns to help us make a trade decision. For example, suppose you find that Data Call has exhibited high autocorrelation historically, and you observe that the pink sheet is moving up for the past few days. In that case, you can expect the price movement to match the lagging time series.
Current and Lagged Values |
| Timeline |
Data Call regressed lagged prices vs. current prices
Serial correlation can be approximated by using the Durbin-Watson (DW) test. The correlation can be either positive or negative. If Data Call pink sheet is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Data Call pink sheet is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Data Call pink sheet over time.
Current vs Lagged Prices |
| Timeline |
Data Call Lagged Returns
When evaluating Data Call's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Data Call pink sheet have on its future price. Data Call autocorrelation represents the degree of similarity between a given time horizon and a lagged version of the same horizon over the previous time interval. In other words, Data Call autocorrelation shows the relationship between Data Call pink sheet current value and its past values and can show if there is a momentum factor associated with investing in Data Call Technologi.
Regressed Prices |
| Timeline |
Thematic Opportunities
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Additional Tools for Data Pink Sheet Analysis
When running Data Call's price analysis, check to measure Data Call's market volatility, profitability, liquidity, solvency, efficiency, growth potential, financial leverage, and other vital indicators. We have many different tools that can be utilized to determine how healthy Data Call is operating at the current time. Most of Data Call's value examination focuses on studying past and present price action to predict the probability of Data Call's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Data Call's price. Additionally, you may evaluate how the addition of Data Call to your portfolios can decrease your overall portfolio volatility.